1. Field of the Invention
This invention relates generally to semiconductor processing, and, more particularly, to detecting disturbances and determining disturbance types during semiconductor processing.
2. Description of the Related Art
Statistical process control (SPC) is commonly used to monitor semiconductor processing tools based on measurements of parameters associated with features formed by the processing tools. For example, an etching process may be monitored by measuring depths of features formed on each semiconductor wafer in a lot of etched wafers. The parameters may be plotted on a statistical process control chart, e.g., as a function of processing lot or run. For example, the statistical process control chart may be formed by plotting the actual measured depths for features formed on a plurality of wafers. In some cases, operating recipes used for the processing tools may be modified during a processing run. The modifications may result in changes to the parameters of the features formed using the processes, such as a depth of an etched feature. Accordingly, a generalized statistical process control chart may plot values of the measured depths that are corrected for the expected changes in the parameters.
Although a certain amount of random variation in the parameters is expected, deviations of one or more parameters from a target value may indicate undesirable and/or unexpected operation of the processing tool. Accordingly, the statistical process control chart (or the generalized statistical process control chart) may be examined for outlier points that deviate from a target value by an amount that is larger than expected for normal random variations of the associated parameter. For example, the statistical process control chart may be visually inspected by an engineer for outlier points. Alternatively, the statistical process control chart may be analyzed using statistical techniques. For example, an outlier point may be used as an indication that a disturbance has occurred in the processing. Accordingly, the outlier point may be used as a trigger for further analysis and determination of corresponding actions that may be used to address the issue.
Conventional algorithms for analyzing the statistical process chart calculate a posteriori, i.e., after the fact, probability that the value of the outlier point indicates a step and/or impulse disturbance in the processing. However, the posteriori probability associated with the outlier point rarely, if ever, contains enough information to discriminate between a step disturbance and an impulse disturbance. Accordingly, conventional algorithms may select a second point associated with a feature formed after the feature associated with the outlier point and calculate a posteriori probability that the value of the second point indicates a step and/or impulse disturbance in the processing. If the posteriori probability associated with second point does not contain enough information to discriminate between a step disturbance and an impulse disturbance, another point may be selected and analyzed. This point-by-point process continues until the posteriori probability associated with one of the points increases above a predetermined threshold. In addition to the aforementioned requirement of an outlier detection algorithm (for example, a generalized SPC chart) to trigger the analysis, conventional algorithms for detecting step and/or impulse disturbances typically require a delay of 4 to 5 lots before the posteriori probability can discriminate between a step disturbance and an impulse disturbance.
The amplitude of the deviation in the outlier point required to trigger conventional disturbance detection algorithms for analyzing the statistical process chart is typically large enough to trigger an alarm condition in the associated processing tool. Consequently, the conventional disturbance detection algorithm may miss some early warning signals until they become severe enough to trigger the SPC alarm. Accordingly, conventional disturbance detection algorithms may be inappropriate for closed-loop control of the processing tool because closed-loop control algorithms reduce variations in the measured parameters and thus the alarm condition will not be triggered in most cases.
The present invention is directed to addressing the effects of one or more of the problems set forth above.